Extract rows / columns of a matrix into separate variables

Question

The following question came up in my course yesterday:

Suppose I have a matrix M = rand(3, 10) that comes out of a calculation, e.g. an ODE solver.

In Python, you can do

x, y, z = M

to extract the rows of M into the three variables, e.g. for plotting with matplotlib.

In Julia we could do

M = M'  # transpose 
x = M[:, 1]
y = M[:, 2]
z = M[:, 3]

Is there a nicer way to do this extraction? It would be nice to be able to write at least (approaching Python)

x, y, z = columns(M)

or

x, y, z = rows(M)

One way would be

columns(M) = [ M[:,i] for i in 1:size(M, 2) ]

but this will make an expensive copy of all the data.

To avoid this would we need a new iterator type, ColumnIterator, that returns slices? Would this be useful for anything other than using this nice syntax?

Answer 1

columns(M) = [ slice(M,:,i) for i in 1:size(M, 2) ]

and

columns(M) = [ sub(M,:,i) for i in 1:size(M, 2) ]

They both return a view, but slice drops all dimensions indexed with scalars.